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GeezerVison is showing github.com — DLQR and DLQE by sawyerbfuller · Pull Request #670 · python-control/python-control

DLQR and DLQE #670

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Merged
murrayrm merged 18 commits into python-control:master from sawyerbfuller:dlqr2
Dec 31, 2021

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Merged

DLQR and DLQE #670

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e2d8f9d
added link to lqe (linear quadratic estimator) function in docs
sawyerbfuller May 19, 2020
0854ee4
Merge branch 'master' of https://github.com/python-control/python-con…
murrayrm Jul 11, 2020
4c79cb2
Merge branch 'master' of https://github.com/sawyerbfuller/python-control
murrayrm Dec 26, 2021
7076fac
Merge branch 'master' of https://github.com/python-control/python-con…
murrayrm Dec 26, 2021
b382f2d
enable non-slycot lqr
sawyerbfuller Nov 9, 2021
04cfe65
initial addition of dlqe and dlqr
sawyerbfuller Nov 9, 2021
0fa431c
dare and care now use scipy routines if slycot not available. fixed b…
sawyerbfuller Nov 9, 2021
0af8f83
enabled some non-slycot testing of dare and care functions in mateqn.py
sawyerbfuller Nov 9, 2021
798ccd5
change exceptions to controlDimension instead of controlArgument for …
sawyerbfuller Nov 9, 2021
88960af
correct the expected error type in mateqn_test.py
sawyerbfuller Nov 9, 2021
90ad3a6
one more error type correction
sawyerbfuller Nov 9, 2021
e26f765
shortened testing code as suggested by @bnavigator
sawyerbfuller Nov 9, 2021
3e99742
enable non-slycot testing + minor cleanup after rebase
murrayrm Dec 26, 2021
20b0312
add lqr/lqe overload for discrete time systems
murrayrm Dec 26, 2021
cf3c9b2
remove redundant argument process in care/dare + fix up error strings
murrayrm Dec 27, 2021
f1f5375
remove _dare_slycot and make slycot/scipy structure moer uniform
murrayrm Dec 27, 2021
fdd399f
require StateSpace for lqr/lqe first arg + process uniformly
murrayrm Dec 27, 2021
0d4ff4c
Fix lqe docstring per @sawyerbfuller
murrayrm Dec 27, 2021
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158 changes: 55 additions & 103 deletions 158 control/mateqn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,7 @@
# Implementation of the functions lyap, dlyap, care and dare
# for solution of Lyapunov and Riccati equations.
#
# Author: Bjorn Olofsson
# Original author: Bjorn Olofsson

# Copyright (c) 2011, All rights reserved.

Expand Down Expand Up @@ -162,6 +162,7 @@ def lyap(A, Q, C=None, E=None, method=None):
_check_shape("Q", Q, n, n, square=True, symmetric=True)

if method == 'scipy':
# Solve the Lyapunov equation using SciPy
return sp.linalg.solve_continuous_lyapunov(A, -Q)

# Solve the Lyapunov equation by calling Slycot function sb03md
Expand All @@ -177,6 +178,7 @@ def lyap(A, Q, C=None, E=None, method=None):
_check_shape("C", C, n, m)

if method == 'scipy':
# Solve the Sylvester equation using SciPy
return sp.linalg.solve_sylvester(A, Q, -C)

# Solve the Sylvester equation by calling the Slycot function sb04md
Expand Down Expand Up @@ -293,6 +295,7 @@ def dlyap(A, Q, C=None, E=None, method=None):
_check_shape("Q", Q, n, n, square=True, symmetric=True)

if method == 'scipy':
# Solve the Lyapunov equation using SciPy
return sp.linalg.solve_discrete_lyapunov(A, Q)

# Solve the Lyapunov equation by calling the Slycot function sb03md
Expand Down Expand Up @@ -343,7 +346,8 @@ def dlyap(A, Q, C=None, E=None, method=None):
# Riccati equation solvers care and dare
#

def care(A, B, Q, R=None, S=None, E=None, stabilizing=True, method=None):
def care(A, B, Q, R=None, S=None, E=None, stabilizing=True, method=None,
A_s="A", B_s="B", Q_s="Q", R_s="R", S_s="S", E_s="E"):
"""X, L, G = care(A, B, Q, R=None) solves the continuous-time
algebraic Riccati equation

Expand Down Expand Up @@ -395,24 +399,6 @@ def care(A, B, Q, R=None, S=None, E=None, stabilizing=True, method=None):
# Decide what method to use
method = _slycot_or_scipy(method)

if method == 'slycot':
# Make sure we can import required slycot routines
try:
from slycot import sb02md
except ImportError:
raise ControlSlycot("Can't find slycot module 'sb02md'")

try:
from slycot import sb02mt
except ImportError:
raise ControlSlycot("Can't find slycot module 'sb02mt'")

# Make sure we can find the required slycot routine
try:
from slycot import sg02ad
except ImportError:
raise ControlSlycot("Can't find slycot module 'sg02ad'")

# Reshape input arrays
A = np.array(A, ndmin=2)
B = np.array(B, ndmin=2)
Expand All @@ -428,10 +414,10 @@ def care(A, B, Q, R=None, S=None, E=None, stabilizing=True, method=None):
m = B.shape[1]

# Check to make sure input matrices are the right shape and type
_check_shape("A", A, n, n, square=True)
_check_shape("B", B, n, m)
_check_shape("Q", Q, n, n, square=True, symmetric=True)
_check_shape("R", R, m, m, square=True, symmetric=True)
_check_shape(A_s, A, n, n, square=True)
_check_shape(B_s, B, n, m)
_check_shape(Q_s, Q, n, n, square=True, symmetric=True)
_check_shape(R_s, R, m, m, square=True, symmetric=True)

# Solve the standard algebraic Riccati equation
if S is None and E is None:
Expand All @@ -446,9 +432,16 @@ def care(A, B, Q, R=None, S=None, E=None, stabilizing=True, method=None):
E, _ = np.linalg.eig(A - B @ K)
return _ssmatrix(X), E, _ssmatrix(K)

# Create back-up of arrays needed for later computations
R_ba = copy(R)
B_ba = copy(B)
# Make sure we can import required slycot routines
try:
from slycot import sb02md
except ImportError:
raise ControlSlycot("Can't find slycot module 'sb02md'")

try:
from slycot import sb02mt
except ImportError:
raise ControlSlycot("Can't find slycot module 'sb02mt'")

# Solve the standard algebraic Riccati equation by calling Slycot
# functions sb02mt and sb02md
Expand All @@ -458,7 +451,7 @@ def care(A, B, Q, R=None, S=None, E=None, stabilizing=True, method=None):
X, rcond, w, S_o, U, A_inv = sb02md(n, A, G, Q, 'C', sort=sort)

# Calculate the gain matrix G
G = solve(R_ba, B_ba.T) @ X
G = solve(R, B.T) @ X

# Return the solution X, the closed-loop eigenvalues L and
# the gain matrix G
Expand All @@ -471,8 +464,8 @@ def care(A, B, Q, R=None, S=None, E=None, stabilizing=True, method=None):
E = np.eye(A.shape[0]) if E is None else np.array(E, ndmin=2)

# Check to make sure input matrices are the right shape and type
_check_shape("E", E, n, n, square=True)
_check_shape("S", S, n, m)
_check_shape(E_s, E, n, n, square=True)
_check_shape(S_s, S, n, m)

# See if we should solve this using SciPy
if method == 'scipy':
Expand All @@ -485,11 +478,11 @@ def care(A, B, Q, R=None, S=None, E=None, stabilizing=True, method=None):
eigs, _ = sp.linalg.eig(A - B @ K, E)
return _ssmatrix(X), eigs, _ssmatrix(K)

# Create back-up of arrays needed for later computations
R_b = copy(R)
B_b = copy(B)
E_b = copy(E)
S_b = copy(S)
# Make sure we can find the required slycot routine
try:
from slycot import sg02ad
except ImportError:
raise ControlSlycot("Can't find slycot module 'sg02ad'")

# Solve the generalized algebraic Riccati equation by calling the
# Slycot function sg02ad
Expand All @@ -504,14 +497,15 @@ def care(A, B, Q, R=None, S=None, E=None, stabilizing=True, method=None):
L = np.array([(alfar[i] + alfai[i]*1j) / beta[i] for i in range(n)])

# Calculate the gain matrix G
G = solve(R_b, B_b.T @ X @ E_b + S_b.T)
G = solve(R, B.T @ X @ E + S.T)

# Return the solution X, the closed-loop eigenvalues L and
# the gain matrix G
return _ssmatrix(X), L, _ssmatrix(G)

def dare(A, B, Q, R, S=None, E=None, stabilizing=True, method=None):
"""(X, L, G) = dare(A, B, Q, R) solves the discrete-time algebraic Riccati
def dare(A, B, Q, R, S=None, E=None, stabilizing=True, method=None,
A_s="A", B_s="B", Q_s="Q", R_s="R", S_s="S", E_s="E"):
"""X, L, G = dare(A, B, Q, R) solves the discrete-time algebraic Riccati
equation

:math:`A^T X A - X - A^T X B (B^T X B + R)^{-1} B^T X A + Q = 0`
Expand All @@ -521,15 +515,17 @@ def dare(A, B, Q, R, S=None, E=None, stabilizing=True, method=None):
matrix G = (B^T X B + R)^-1 B^T X A and the closed loop eigenvalues L,
i.e., the eigenvalues of A - B G.

(X, L, G) = dare(A, B, Q, R, S, E) solves the generalized discrete-time
X, L, G = dare(A, B, Q, R, S, E) solves the generalized discrete-time
algebraic Riccati equation

:math:`A^T X A - E^T X E - (A^T X B + S) (B^T X B + R)^{-1} (B^T X A + S^T) + Q = 0`

where A, Q and E are square matrices of the same dimension. Further, Q and
R are symmetric matrices. The function returns the solution X, the gain
matrix :math:`G = (B^T X B + R)^{-1} (B^T X A + S^T)` and the closed loop
eigenvalues L, i.e., the eigenvalues of A - B G , E.
where A, Q and E are square matrices of the same dimension. Further, Q
and R are symmetric matrices. If R is None, it is set to the identity
matrix. The function returns the solution X, the gain matrix :math:`G =
(B^T X B + R)^{-1} (B^T X A + S^T)` and the closed loop eigenvalues L,
i.e., the (generalized) eigenvalues of A - B G (with respect to E, if
specified).

Parameters
----------
Expand Down Expand Up @@ -575,87 +571,43 @@ def dare(A, B, Q, R, S=None, E=None, stabilizing=True, method=None):
m = B.shape[1]

# Check to make sure input matrices are the right shape and type
_check_shape("A", A, n, n, square=True)
_check_shape(A_s, A, n, n, square=True)
_check_shape(B_s, B, n, m)
_check_shape(Q_s, Q, n, n, square=True, symmetric=True)
_check_shape(R_s, R, m, m, square=True, symmetric=True)
if E is not None:
_check_shape(E_s, E, n, n, square=True)
if S is not None:
_check_shape(S_s, S, n, m)

# Figure out how to solve the problem
if method == 'scipy' and not stabilizing:
raise ControlArgument(
"method='scipy' not valid when stabilizing is not True")

elif method == 'slycot':
return _dare_slycot(A, B, Q, R, S, E, stabilizing)
if method == 'scipy':
if not stabilizing:
raise ControlArgument(
"method='scipy' not valid when stabilizing is not True")

else:
_check_shape("B", B, n, m)
_check_shape("Q", Q, n, n, square=True, symmetric=True)
_check_shape("R", R, m, m, square=True, symmetric=True)
if E is not None:
_check_shape("E", E, n, n, square=True)
if S is not None:
_check_shape("S", S, n, m)

Rmat = _ssmatrix(R)
Qmat = _ssmatrix(Q)
X = sp.linalg.solve_discrete_are(A, B, Qmat, Rmat, e=E, s=S)
X = sp.linalg.solve_discrete_are(A, B, Q, R, e=E, s=S)
if S is None:
G = solve(B.T @ X @ B + Rmat, B.T @ X @ A)
G = solve(B.T @ X @ B + R, B.T @ X @ A)
else:
G = solve(B.T @ X @ B + Rmat, B.T @ X @ A + S.T)
G = solve(B.T @ X @ B + R, B.T @ X @ A + S.T)
if E is None:
L = eigvals(A - B @ G)
else:
L, _ = sp.linalg.eig(A - B @ G, E)

return _ssmatrix(X), L, _ssmatrix(G)


def _dare_slycot(A, B, Q, R, S=None, E=None, stabilizing=True):
# Make sure we can import required slycot routine
try:
from slycot import sb02md
except ImportError:
raise ControlSlycot("Can't find slycot module 'sb02md'")

try:
from slycot import sb02mt
except ImportError:
raise ControlSlycot("Can't find slycot module 'sb02mt'")

# Make sure we can find the required slycot routine
try:
from slycot import sg02ad
except ImportError:
raise ControlSlycot("Can't find slycot module 'sg02ad'")

# Reshape input arrays
A = np.array(A, ndmin=2)
B = np.array(B, ndmin=2)
Q = np.array(Q, ndmin=2)
R = np.eye(B.shape[1]) if R is None else np.array(R, ndmin=2)

# Determine main dimensions
n = A.shape[0]
m = B.shape[1]

# Initialize optional matrices
S = np.zeros((n, m)) if S is None else np.array(S, ndmin=2)
E = np.eye(A.shape[0]) if E is None else np.array(E, ndmin=2)

# Check to make sure input matrices are the right shape and type
_check_shape("A", A, n, n, square=True)
_check_shape("B", B, n, m)
_check_shape("Q", Q, n, n, square=True, symmetric=True)
_check_shape("R", R, m, m, square=True, symmetric=True)
_check_shape("E", E, n, n, square=True)
_check_shape("S", S, n, m)

# Create back-up of arrays needed for later computations
A_b = copy(A)
R_b = copy(R)
B_b = copy(B)
E_b = copy(E)
S_b = copy(S)

# Solve the generalized algebraic Riccati equation by calling the
# Slycot function sg02ad
sort = 'S' if stabilizing else 'U'
Expand All @@ -669,7 +621,7 @@ def _dare_slycot(A, B, Q, R, S=None, E=None, stabilizing=True):
L = np.array([(alfar[i] + alfai[i]*1j) / beta[i] for i in range(n)])

# Calculate the gain matrix G
G = solve(B_b.T @ X @ B_b + R_b, B_b.T @ X @ A_b + S_b.T)
G = solve(B.T @ X @ B + R, B.T @ X @ A + S.T)

# Return the solution X, the closed-loop eigenvalues L and
# the gain matrix G
Expand Down
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